Towards 360 VR Sickness Mitigation: From Virtual Reality Eye-tracking to Visual Communication

虚拟现实 计算机科学 模拟病 眼动 可视化 人机交互 数据可视化 多媒体 计算机视觉 视觉传达 计算机图形学(图像) 人工智能
作者
Jeonghaeng Lee,Woojae Kim,Chao Yang,Ping An,Sanghoon Lee
出处
期刊:IEEE Transactions on Visualization and Computer Graphics [Institute of Electrical and Electronics Engineers]
卷期号:: 1-13
标识
DOI:10.1109/tvcg.2024.3447838
摘要

Most 360 virtual reality (VR) contents have been developed without considering that users could be affected by VR sickness. Accordingly, users' viewing safety has been steadily highlighted as a critical problem in the VR market. In this study, we investigate a novel VR sickness mitigation framework based on human visual characteristics for the rendered VR content. First, we build a large-scale 360 VR content database termed VRSP360 (VR Sickness and Presence 360) dedicated to the analysis of VR sickness and thoroughly conduct eye-tracking experiments to measure human perception. In the experiment, we observe that the users' gaze distribution is highly center-biased when they experience excessive VR sickness. From this observation, we design a foveated filtering framework that limits high-frequency textures in the peripheral view to mitigate VR sickness. Particularly, given the human visual system's (HVS) non-uniform resolution with respect to the fovea, we also adopt the foveation-based filtering method using the trade-off between sickness mitigation and presence conservation, which reduces any loss in perceptual quality despite the filtering. We further demonstrate that our framework can effectively compress visual information by applying foveated compression. In addition, we develop two metrics (visual texture index and perceptual information index) to measure the effective preservation of user-perceived information despite the filtration of peripheral vision textures by our proposed mitigation method. Through rigorous subjective evaluation on both original content and its VR-sickness-mitigated version, we demonstrate that the proposed framework successfully mitigates VR sickness with a reduction rate of ∼ 19% on the proposed dataset.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
小胖wwwww完成签到 ,获得积分10
3秒前
4秒前
8D完成签到,获得积分10
5秒前
儒雅的念烟完成签到 ,获得积分10
5秒前
小灰灰完成签到,获得积分0
5秒前
6秒前
8秒前
苹果梦蕊完成签到 ,获得积分10
8秒前
steraphia发布了新的文献求助10
8秒前
arniu2008应助初景采纳,获得30
9秒前
我是老大应助谭平采纳,获得10
10秒前
不吃葱花行不行完成签到 ,获得积分10
11秒前
敏感的飞松完成签到 ,获得积分10
11秒前
LSQ47完成签到,获得积分10
11秒前
bakerwm发布了新的文献求助10
13秒前
13秒前
arniu2008应助初景采纳,获得30
13秒前
15秒前
18秒前
ZZU1997发布了新的文献求助10
19秒前
谭平完成签到,获得积分10
19秒前
萧萧完成签到,获得积分10
19秒前
天道酬勤完成签到,获得积分10
20秒前
大个应助小荷才露尖尖角采纳,获得10
22秒前
cccc完成签到,获得积分10
22秒前
谭平发布了新的文献求助10
22秒前
25秒前
ljc完成签到,获得积分10
27秒前
28秒前
28秒前
hr完成签到 ,获得积分10
29秒前
511完成签到 ,获得积分10
29秒前
30秒前
时势造英雄完成签到 ,获得积分10
32秒前
33秒前
34秒前
34秒前
大方念云完成签到 ,获得积分10
34秒前
Canmiyo完成签到 ,获得积分10
35秒前
小费完成签到 ,获得积分10
36秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
化工安全与环保 1000
Autoparametric Resonance in Mechanical Systems 1000
基于锂离子电池正极材料回收的绿色溶剂开发及工程化应用研究 800
Effects of Two Weeks of Red Light Therapy on Choroidal Thickness and Axial Length in Young Adults 700
Cosmos as Art Object: Studies in Plato's Timaeus and Other Dialogues 600
Management and the Arts 510
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7656682
求助须知:如何正确求助?哪些是违规求助? 9227328
关于积分的说明 19828993
捐赠科研通 7223096
什么是DOI,文献DOI怎么找? 3280333
关于科研通互助平台的介绍 2440621
邀请新用户注册赠送积分活动 2280175